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NIPS
2007
15 years 6 months ago
Convex Learning with Invariances
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
HYBRID
2005
Springer
15 years 11 months ago
Learning Multi-modal Control Programs
Abstract. Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the contr...
Tejas R. Mehta, Magnus Egerstedt
IJCAI
2007
15 years 6 months ago
Analogical Learning in a Turn-Based Strategy Game
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
Thomas R. Hinrichs, Kenneth D. Forbus
ECML
2004
Springer
15 years 10 months ago
Convergence and Divergence in Standard and Averaging Reinforcement Learning
Although tabular reinforcement learning (RL) methods have been proved to converge to an optimal policy, the combination of particular conventional reinforcement learning techniques...
Marco Wiering
146
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ICML
1999
IEEE
15 years 9 months ago
Learning Hierarchical Performance Knowledge by Observation
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Michael van Lent, John E. Laird